Conserved immuno-collagenic subtypes predict response to immune checkpoint blockade.

BACKGROUND: Immune checkpoint blockade (ICB) has revolutionized the treatment of various cancer types. Despite significant preclinical advancements in understanding mechanisms, identifying the molecular basis and predictive biomarkers for clinical ICB responses remains challenging. Recent evidence, both preclinical and clinical, underscores the pivotal role of the extracellular matrix (ECM) in modulating immune cell infiltration and behaviors. This study aimed to create an innovative classifier that leverages ECM characteristics to enhance the effectiveness of ICB therapy. METHODS: We analyzed transcriptomic collagen activity and immune signatures in 649 patients with cancer undergoing ICB therapy. This analysis led to the identification of three distinct immuno-collagenic subtypes predictive of ICB responses. We validated these subtypes using the transcriptome data from 9,363 cancer patients from The Cancer Genome Atlas (TCGA) dataset and 1,084 in-house samples. Additionally, novel therapeutic targets were identified based on these established immuno-collagenic subtypes. RESULTS: Our categorization divided tumors into three subtypes: "soft & hot" (low collagen activity and high immune infiltration), "armored & cold" (high collagen activity and low immune infiltration), and "quiescent" (low collagen activity and immune infiltration). Notably, "soft & hot" tumors exhibited the most robust response to ICB therapy across various cancer types. Mechanistically, inhibiting collagen augmented the response to ICB in preclinical models. Furthermore, these subtypes demonstrated associations with immune activity and prognostic predictive potential across multiple cancer types. Additionally, an unbiased approach identified B7 homolog 3 (B7-H3), an available drug target, as strongly expressed in "armored & cold" tumors, relating with poor prognosis. CONCLUSION: This study introduces histopathology-based universal immuno-collagenic subtypes capable of predicting ICB responses across diverse cancer types. These findings offer insights that could contribute to tailoring personalized immunotherapeutic strategies for patients with cancer.

A promising target for breast cancer: B7-H3.

Breast cancer (BC) is the second-leading factor of mortality for women globally and is brought on by a variety of genetic and environmental causes. The conventional treatments for this disease have limitations, making it difficult to improve the lifespan of breast cancer patients. As a result, extensive research has been conducted over the past decade to find innovative solutions to these challenges. Targeting of the antitumor immune response through the immunomodulatory checkpoint protein B7 family has revolutionized cancer treatment and led to intermittent patient responses. B7-H3 has recently received attention because of its significant demodulation and its immunomodulatory effects in many cancers. Uncontrolled B7-H3 expression and a bad outlook are strongly associated, according to a substantial body of cancer research. Numerous studies have shown that BC has significant B7-H3 expression, and B7-H3 induces an immune evasion phenotype, consequently enhancing the survival, proliferation, metastasis, and drug resistance of BC cells. Thus, an innovative target for immunotherapy against BC may be the B7-H3 checkpoint.In this review, we discuss the structure and regulation of B7-H3 and its double costimulatory/coinhibitory function within the framework of cancer and normal physiology. Then we expound the malignant behavior of B7-H3 in BC and its role in the tumor microenvironment (TME) and finally focus on targeted drugs against B7-H3 that have opened new therapeutic opportunities in BC.

Associations between HIFs and tumor immune checkpoints: mechanism and therapy.

Hypoxia, which activates a variety of signaling pathways to enhance tumor cell growth and metabolism, is among the primary features of tumor cells. Hypoxia-inducible factors (HIFs) have a substantial impact on a variety of facets of tumor biology, such as epithelial-mesenchymal transition, metabolic reprogramming, angiogenesis, and improved radiation resistance. HIFs induce hypoxia-adaptive responses in tumor cells. Many academics have presented preclinical and clinical research targeting HIFs in tumor therapy, highlighting the potential applicability of targeted HIFs. In recent years, the discovery of numerous pharmacological drugs targeting the regulatory mechanisms of HIFs has garnered substantial attention. Additionally, HIF inhibitors have attained positive results when used in conjunction with traditional oncology radiation and/or chemotherapy, as well as with the very promising addition of tumor immunotherapy. Immune checkpoint inhibitors (CPIs), which are employed in a range of cancer treatments over the past decades, are essential in tumor immunotherapy. Nevertheless, the use of immunotherapy has been severely hampered by tumor resistance and treatment-related toxicity. According to research, HIF inhibitors paired with CPIs may be game changers for multiple malignancies, decreasing malignant cell plasticity and cancer therapy resistance, among other things, and opening up substantial new pathways for immunotherapy drug development. The structure, activation mechanisms, and pharmacological sites of action of the HIF family are briefly reviewed in this work. This review further explores the interactions between HIF inhibitors and other tumor immunotherapy components and covers the potential clinical use of HIF inhibitors in combination with CPIs.

Secreted proteins in plasma and placenta as novel non-invasive biomarkers for intrahepatic cholestasis of pregnancy: A case-control study.

Background: Intrahepatic cholestasis of pregnancy (ICP) is likely to lead to unfavorable consequences. Total bile acid (TBA) is thought to be the sole ICP indicator available as of now, but it comes with some kind of restrictions in terms of sensitivity and specificity. We were endeavoring to find potential diagnostic biomarkers for ICP in this investigation. Methods: This case-control study with a prospective nature included 40 females in the stage of pregnancy who were diagnosed with ICP. It also included another 20 females who were also pregnant but with sound physical condition(control). Placental and plasma samples were collected from all females that were in the stage of pregnancy, except for 20 ICP patients, in which only plasma was collected. We used four-dimensional data-independent acquisition followed by enzyme-linked immunosorbent assay and immunohistochemistry to identify and validate plasma and placental profiles in ICP patients and controls. Bioinformatics was adopted in an effort to demonstrate the relevant biological processes and signalling pathways. Correlation analysis was used to analyse the consistency of tissue and plasma protein expression and the correlation between sequencing and experimental results. Results: The expression levels of nectin-1 (NECTIN1), Kunitz-type protease inhibitor 1 (SPINT1), and inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3) were remarkably higher in ICP patients than in controls. However, heparin cofactor 2 (SERPIND1) expression levels in female participants in the stage of pregnancy who were diagnosed with ICP were remarkably lower than those pregnant females with good physical fitness. In addition to the negative correlation between SERPIND1 and TBA, NECTIN1, SPINT1, and ITIH3 expression positively correlated with TBA. Area under the receiver operating characteristic curve (AUC) values of 0.7925, 0.8313, 0.8163, and 0.9025, respectively, were used to assess the diagnostic accuracies of NECTIN1, SPINT1, ITIH3, and SERPIND1. AUC (0.9438) was considerably greater when NECTIN1, SPINT1, and SERPIND1 were integrated, according to binary logistic regression. The AUC of the ROC curve for various combinations of SERPIND1 and other indicators was higher than itself, thus providing a more reliable ICP diagnosis. Furthermore, according to the bioinformatics analysis, the NECTIN1, SPINT1, ITIH3, and SERPIND1 were identified as secreted proteins because they were localized in the extracellular region. Conclusions: This research discovered new non-invasive ICP indicators. On top of this, it sheds new light on the crucial diagnostic function of secreted proteins in ICP.

The heterogeneity of tumour immune microenvironment revealing the CRABP2/CD69 signature discriminates distinct clinical outcomes in breast cancer.

BACKGROUND: It has been acknowledged that the tumour immune microenvironment (TIME) plays a critical role in determining therapeutic responses and clinical outcomes in breast cancer (BrCa). Thus, the identification of the TIME features is essential for guiding therapy and prognostic assessment for BrCa. METHODS: The heterogeneous cellular composition of the TIME in BrCa by single-cell RNA sequencing (scRNA-seq). Two subtype-special genes upregulated in the tumour-rich subtype and the immune-infiltrating subtype were extracted, respectively. The CRABP2/CD69 signature was established based on CRABP2 and CD69 expression, and its predictive values for the clinical outcome and the neoadjuvant chemotherapy (NAT) responses were validated in multiple cohorts. Moreover, the oncogenic role of CRABP2 was explored in BrCa cells. RESULTS: Based on the heterogeneous cellular composition of the TIME in BrCa, the BrCa samples could be divided into the tumour-rich subtype and the immune-infiltrating subtype, which exhibited distinct prognosis and chemotherapeutic responses. Next, we extracted CRABP2 as the biomarker for the tumour-rich subtype and CD69 as the biomarker for the immune-infiltrating subtype. Based on the CRABP2/CD69 signature, BrCa samples were re-divided into three subtypes, and the CRABP2highCD69low subtype exhibited the worst prognosis and the lowest chemotherapeutic response, while the CRABP2lowCD69high subtype showed the opposite results. Furthermore, CARBP2 functioned as a novel oncogene in BrCa, which promoted tumour cell proliferation, migration, and invasion, and CRABP2 inhibition triggered the activation of cytotoxic T lymphocytes (CTLs). CONCLUSION: The CRABP2/CD69 signature is significantly associated with the TIME features and could effectively predict the clinical outcome. Also, CRABP2 is determined to be a novel oncogene, which could be a therapeutic target in BrCa.

The emerging role of PPAR-alpha in breast cancer.

Breast cancer has been confirmed to have lipid disorders in the tumour microenvironment. Peroxisome proliferator-activated receptor alpha (PPARα) is a ligand-activated transcriptional factor that belongs to the family of nuclear receptors. PPARα regulates the expression of genes involved in fatty acid homeostasis and is a major regulator of lipid metabolism. Because of its effects on lipid metabolism, an increasing number of studies have investigated the relationship of PPARα with breast cancer. PPARα has been shown to impact the cell cycle and apoptosis in normal cells and tumoral cells through regulating genes of the lipogenic pathway, fatty acid oxidation, fatty acid activation, and uptake of exogenous fatty acids. Besides, PPARα is involved in the regulation of the tumour microenvironment (anti-inflammation and inhibition of angiogenesis) by modulating different signal pathways such as NF-κB and PI3K/AKT/mTOR. Some synthetic PPARα ligands are used in adjuvant therapy for breast cancer. PPARα agonists are reported to reduce the side effects of chemotherapy and endocrine therapy. In addition, PPARα agonists enhance the curative effects of targeted therapy and radiation therapy. Interestingly, with the emerging role of immunotherapy, attention has been focused on the tumour microenvironment. The dual functions of PPARα agonists in immunotherapy need further research. This review aims to consolidate the operations of PPARα in lipid-related and other ways, as well as discuss the current and potential applications of PPARα agonists in tackling breast cancer.

An omics review and perspective of researches on intrahepatic cholestasis of pregnancy.

Intrahepatic cholestasis of pregnancy (ICP) is one of the common pregnancy complications that may threaten the health of both pregnant women and their fetuses. Hence, it is of vital importance to identify key moleculars and the associated functional pathways of ICP, which will help us to better understand the pathological mechanisms as well as to develop precise clinical biomarkers. The emerging and developing of multiple omics approaches enable comprehensive studies of the genome, transcriptome, proteome and metabolome of clinical samples. The present review collected and summarized the omics based studies of ICP, aiming to provide an overview of the current progress, limitations and future directions. Briefly, these studies covered a broad range of research contents by the comparing of different experimental groups including ICP patients, ICP subtypes, ICP fetuses, ICP models and other complications. Correspondingly, the studied samples contain various types of clinical samples, in vitro cultured tissues, cell lines and the samples from animal models. According to the main research objectives, we further categorized these studies into two groups: pathogenesis and diagnosis analyses. The pathogenesis studies identified tens of functional pathways that may represent the key regulatory events for the occurrence, progression, treatment and fetal effects of ICP. On the other hand, the diagnosis studies tested more than 40 potential models for the early-prediction, diagnosis, grading, prognosis or differential diagnosis of ICP. Apart from these achievements, we also evaluated the limitations of current studies, and emphasized that many aspects of clinical characteristics, sample processing, and analytical method can greatly affect the reliability and repeatability of omics results. Finally, we also pointed out several new directions for the omics based analyses of ICP and other perinatal associated conditions in the future.

Real-time distance and velocity measurement based on the dual-comb system.

With the development of laser metrology, the dual-comb system has natural superiority in the measuring fields. Specifically, distance and velocity represent a basic state for the target in space. We propose an application mode of the dual-comb interferometry integrated into the field programmable gate array. A high-speed parallel processor truly gives full play to the benefit of the data processing rate. The algorithm of the peak extraction and the address matching also bring an efficient working mode into the whole scheme. To verify the performance of this system, we devise a series of experiments for distance and velocity, respectively. The data processing rate of the distance is 425 Hz and that of the corresponding average velocity is 0.425 Hz, which is flexible for different measuring conditions. The experimental results show that the difference can be well within 252.8 µm at 5 m range and 284.9 µm/s over 0.5 m/s.

Fast and Accurate 3D Measurement Based on Light-Field Camera and Deep Learning.

The precise combination of image sensor and micro-lens array enables light-field cameras to record both angular and spatial information of incoming light, therefore, one can calculate disparity and depth from one single light-field image captured by one single light-field camera. In turn, 3D models of the recorded objects can be recovered, which means a 3D measurement system can be built using a light-field camera. However, reflective and texture-less areas in light-field images have complicated conditions, making it hard to correctly calculate disparity with existing algorithms. To tackle this problem, we introduce a novel end-to-end network VommaNet to retrieve multi-scale features from reflective and texture-less regions for accurate disparity estimation. Meanwhile, our network has achieved similar or better performance in other regions for both synthetic light-field images and real-world data compared to the state-of-the-art algorithms.

Underwater distance measurement using frequency comb laser.

In this paper, we theoretically and experimentally analyze the frequency-comb interferometry at 518 nm in the underwater environment, which we use to measure the underwater distance with high accuracy and precision. In the time domain, we analyze the principle of pulse cross correlation. The interferograms can be obtained in the vicinity of N∙lpp, where N is an integer and lpp is the pulse-to-pulse length. Due to the strong dispersion of water, the pulse can be broadened as the distance increases. The distance can be measured via the peak position of the interferograms. The experimental results show a difference within 100 µm at 8 m range, compared with the reference values. In the frequency domain, we analyze the principle of dispersive interferometry. The spectrograms can be observed near the location of N∙lpp, due to the low resolution of the optical spectrum analyzer. Because of the strong dispersion of water, the modulation frequency of the spectrogram is not constant. A balanced wavelength will exist with the widest fringe, at which the group optical path difference between the reference and measurement arm is equal to N∙lpp. The position of the widest fringe can be used to measure the distance. Compared with the reference values, the experimental results indicate a difference within 100 µm at 8 m range.